Modeling
Saeed Chehreh; Mohammadali Sarlak; Ashraf Rahimian
Abstract
This research was conducted to design a model to improve the performance of start-up accelerators and identify their dimensions and components. This research is a mixed exploratory research in terms of nature and is applied in terms of purpose. It includes two qualitative (supercomposition and Delphi) ...
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This research was conducted to design a model to improve the performance of start-up accelerators and identify their dimensions and components. This research is a mixed exploratory research in terms of nature and is applied in terms of purpose. It includes two qualitative (supercomposition and Delphi) and quantitative parts. In the qualitative part, the research population was 25 Persian and Latin articles related to the improvement of performance in the accelerator, which were selected by census method with the metacombination mode. The statistical population in the Delphi section included 30 faculty members in management and managers related to start-up accelerators. In the quantitative part, 250 samples of employees of Iranian accelerators were selected using a systematic random stratified method. Data were collected using the researcher's questionnaire, the validity of which was obtained and confirmed by construct validity and factor loadings, as well as the calculation of Cronbach's alpha. For data analysis, exploratory and confirmatory factor analysis and path analysis were used using SPSS and Smart PLS software. According to the results obtained from exploratory factor analysis, 73 questionnaire items were classified into 12 main components and 61 sub-components. The results of confirmatory factor analysis show that 12 human resource components of coaching, management techniques, customer perspective, continuous improvement, support, financial relations, internal processes, business model, program ecosystem, competitors, and environment are effective in improving the performance of start-tup accelerators
Causation
ziba mohammadzadeh; Ali Biranvand; Saeed Chehreh
Abstract
One of the most widely used fields of knowledge management is the commercialization of knowledge. This research, with the help of scientometric techniques, identifies the effects of knowledge in the field of knowledge commercialization. This research is a kind of scientometric. Initial data were obtained ...
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One of the most widely used fields of knowledge management is the commercialization of knowledge. This research, with the help of scientometric techniques, identifies the effects of knowledge in the field of knowledge commercialization. This research is a kind of scientometric. Initial data were obtained from the Web of Science (WoS) database to investigate the historical roots of published works in the field of commercialization of knowledge. Then, the main roots of this filed, the amount of received citations, and influential works were identified using RPYS software. Next, with the help of the yearcr software, the extent of the effects of the works outside of the range of peaks were also introduced. The period under investigation is the publication in the years 1900-2015. By searching published works in the time period of 1900-2015, 1550 records related to commercialization of knowledge were retrieved. The total number of citations up to the time of the present research was 39817, which resulted in the emergence of five peaks in the years 1934, 1962, 1973, 1998, and 2003. The present project has introduced the influential works in the field of commercialization of knowledge. Identifying the influential effects in the field of commercialization of knowledge makes it possible to identify the main origins and subfields of knowledge.
